2nd Workshop on Formal Verification of Machine Learning (WFVML 2023)

Co-located with ICML 2023, at Hawaii Convention Center

Date: July 28 or July 29

Honolulu, Hawaii, United States (Physical Workshop)

About This Workshop (Proposal)

As machine learning-based systems are being deployed in safety-critical applications such as autonomous driving, medical imaging, or cyber-security systems, characterizing their behavior not only in the average but also worst case becomes essential. However, most existing research treats machine learning models such as deep neural networks as black boxes and uses simple empirical metrics such as their mean accuracy to quantify their performance. However, accuracy alone is not sufficient to assure that models conform to even basic safety or robustness specifications. To fill this gap, formal verification algorithms for machine learning aim to formally prove or disprove desired properties of machine learning models, including safety, fault tolerance, fairness, robustness, and correctness. 

The aims of this workshop are:

Our workshop features a diverse panel of invited speakers spanning research backgrounds from robotics and programming languages to optimization and cyber security. Please check out our tentative workshop schedule.

Workshop Organizers

Important Dates